code: def __init__(self, n_d, words, fix_emb=False):
      super(EmbeddingLayer, self).__init__()
      word2id = {}
      for w in words:
          if w not in word2id:
              word2id[w] = len(word2id)
  
      self.word2id = word2id
      self.n_V, self.n_d = len(word2id), n_d
      self.embedding = nn.Embedding(self.n_V, n_d)
  
imports: import sys
  import os
  import argparse
  import time
  import random
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import sru
label_desc: Use image node_id 1 to create a new EmbeddingLayer object from inherited base classes: nn with example: obj = EmbeddingLayer(n_d, words, fix_emb)